Multi-Material Torque Sensor Embedding One-Shot 3D-Printed Deformable Capacitive Structures - Archive ouverte HAL
Article Dans Une Revue IEEE Sensors Letters Année : 2024

Multi-Material Torque Sensor Embedding One-Shot 3D-Printed Deformable Capacitive Structures

Résumé

Measuring interaction forces between robots and humans is a major challenge in physical human-robot interactions. Nowadays, conventional force/torque sensors suffer from bulkiness, high cost, and stiffness, which limit their use in soft robotics. Thus, we introduce a novel torque sensor manufactured with material extrusion technology. Our approach relies on capacitive structures, which are at the same time the deformable and sensing parts of the sensor, making it very compact. These structures are made in one single print, simplifying the manufacturing process compared to traditional torque sensors. The sensor characteristics can be modulated thanks to material extrusion technology. We conduct experiments in a dedicated test bench to characterize the proposed torque sensor. From the characterization results, we implement a torque estimator based on the deformation angle estimate calculated from capacitance changes. The proposed torque sensor is able to measure torques within a +/- 2.5 N.m range with a maximum error of 6% up to a deformation angle velocity of 35 degrees/s. It is also able to measure its deformation angle with a maximum error of 0.4(degrees). The accuracy of our sensor makes it suitable to ensure fine control in physical human-robot interaction applications.
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hal-04699911 , version 1 (27-09-2024)

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Jose Eduardo Aguilar-Segovia, Maxime Manzano, Sylvain Guégan, Ronan Le Breton, Alice Farhi-Rivasseau, et al.. Multi-Material Torque Sensor Embedding One-Shot 3D-Printed Deformable Capacitive Structures. IEEE Sensors Letters, 2024, 8 (9), pp.2503204. ⟨10.1109/LSENS.2024.3440195⟩. ⟨hal-04699911⟩
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